Introduction With the increasing demand on productivity, quality, and availability, machines have become more complex and capital intensive. Developing and implementing a maintenance programme is a difficult process that suffers from many problems. It often suffers from lack of a systematic and a consistent methodology. In addition, since the process of developing the programme relates to diffe...

A large literature shows that strategic interactions among actors with conflicting objectives can cause the political process to produce outcomes that lower welfare. This paper investigates an alternative explanation of such outcomes: if individuals’ errors in assessing the likely effects of proposed policies are correlated, democratic decisionmaking can produce welfare-reducing outcomes even i...

In this paper we integrate the macroscopic traffic flow model METANET with the microscopic dynamic emission and fuel consumption model VT-Micro. We use the integrated models in the model predictive control (MPC) framework to reduce exhaust emissions, fuel consumption, and travel time using dynamic speed limit control. With simulation experiments we demonstrate the countereffects and conflicting...

For optimization of real-world arch dams, it is unavoidable to consider two or more conflicting objectives. This paper employs two multi-objective differential evolution algorithms (MoDE) in combination of a parallel working MATLAB-APDL code to obtain a set of Pareto solutions for optimal shape of arch dams. Full dam-reservoir interaction subjected to seismic loading is considered. A benchmark ...

Dealing with real world engineering problems, often comes with facing multiple and conflicting objectives and requirements. Water distributions systems (WDS) are not exempt from this: while cost and hydraulic performance are usually conflicting objectives, several requirements related with environmental issues in water sources might be in conflict as well. Commonly, optimisation statements are ...

Optimal operation of hydropower reservoir systems often needs to optimize multiple conflicting objectives simultaneously. The conflicting objectives result in a Pareto front, which is a set of non-dominated solutions. Non-dominated solutions cannot outperform each other on all the objectives. An optimization framework based on the multi-swarm comprehensive learning particle swarm optimization a...